Abstract
The study presents the development of classification models for sedimentation of activated sludge using the artificial neural networks (ANN), logistic-regression (RL), and linear discrimination model (LDM). The input consisted of indicators of wastewater quantity and quality (biochemical oxygen demand, chemical oxygen demand, total suspended solids, total nitrogen and total phosphorus at the inflow to the wastewater treatment plant) and operational characteristic of the bioreactor (pH, temperature of activated sludge, mixed liquor suspended solids, concentration of oxygen in the nitrification chamber, amount of PIX dosing).The prediction quality of the developed models was measured with: sensitivity, specificity, and computed errors. The calculations of the sedimentation were performed for sludge volume index (SVI). The results indicate that successful predictions were obtained using ANN, RL and LDM methods, which is supported by the fit of computations to measurement results. The study shows that for the wastewater treatment plant of concern, sedimentation properties can be obtained using only the loads of organic compounds, mixed liquor suspended solids, temperature, pH of activated sludge, concentration of oxygen in the nitrification chamber and amount of PIX dozing. Other analysed variables appear to be statistically insignificant for the sludge volume index.
Highlights
Engineering practice shows that the activated sludge method is one of the most frequently used and most effective technologies of domestic wastewater treatment
That considerably affected the operational parameters of aeration tanks; the value of the mixed liquor suspended solids (MLSS) ranged 1.91–6.59 kg/m3 and oxygen concentration in the nitrification tank changed 0.55–5.78 mg/dm3, whereas the mean value of dissolved oxygen (DO) was 2.56 mg/dm3
On the basis of analyses conducted for the study, it is possible to state that the linear discriminant model, the logit model and artificial neural networks can be applied to the assessment of the settling capacity of the activated sludge
Summary
Engineering practice shows that the activated sludge method is one of the most frequently used and most effective technologies of domestic wastewater treatment. To be able to predict metastable states in good advance, and to make it possible for the treatment plant staff to select optimum settings of the bioreactor parameters to ensure effective wastewater treatment, it is necessary to develop mathematical models that are capable of determining continuous value or the linguistic value. In the former case, the discrete values of the measured dependent variable are predicted [4,5,6]. The ranges of variation of the parameter under analysis, set by the researcher, correspond to those classes [7,8]
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